Caspio is a solution providing the infrastructure, tools and support that allows users to create customized online databases, applications, reports, forms, and charts/graphs. The point-and-click interface requires no coding experience and apps can be integrated into any website, blog, intranet or content management system.
$50
per month
Google BigQuery
Score 8.6 out of 10
N/A
Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$6.25
per TiB (after the 1st 1 TiB per month, which is free)
Pricing
Caspio
Google BigQuery
Editions & Modules
Free
$0
per month
Starter
$50
per month
Professional
$600
per month
Enterprise
$2,250
per month
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
Offerings
Pricing Offerings
Caspio
Google BigQuery
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
> All plans include unlimited users.
> 10% discount when paid annually.
> Caspio offers a 10% discount to non-profits, NGOs, and customers in qualifying countries.
> Compliance plans support strict regulatory requirements: HIPAA; FERPA; PCI DSS Level 1; VPAT 2.0/Section 508; GDPR; EU-US Privacy Shield; SOC 2 Type II; ISO 9001, 27001; CSA Star Level 1, 2 & 3; 3D Secure 2.
> Project consultations for planning and customization, in-depth online help, how-to videos and instructor-led training.
> Pricing plans designed for teams of all sizes.
Contact forms are incredibly easy to build and customize, as are most other kinds of more involved forms. Forms allow html input and can be designed in a number of ways. It's helpful if you know some HTML. JavaScript knowledge can add advanced options, but is not necessary for the most common uses. The company used to call itself "No-Code," but has changed to say "Low Code," which is much more accurate.
Google BigQuery really shines in scenarios requiring real-time analytics on large data streams and predictive analytics with its machine learning integration. Teams have been using it extensively all over. However, it may not be the best fit for organizations dealing with small datasets because of the higher costs. And also, it might not be the best fit for highly complex data transformations, where simpler or more specialized solutions could be more appropriate.
Caspio is an online database platform. It allows one to create multiple tables and views to be stored via the web. Tables can be configured to not only hold data but also to hold files like Word docs and images.
Caspio is great at creating online forms and reports. It allows the user to create forms to capture, update data, whether it's password protected or just a simple form.
As a database platform, one can create online tables and forms linking multiple tables and views to each other. I would say it is the Microsoft Access of the online platforms.
The system is very easy. Wizards allow one to create forms, tables, and datapages. Since the platform is online, you may access your database anywhere.
Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data.
Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns.
Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds.
It is challenging to predict costs due to BigQuery's pay-per-query pricing model. User-friendly cost estimation tools, along with improved budget alerting features, could help users better manage and predict expenses.
The BigQuery interface is less intuitive. A more user-friendly interface, enhanced documentation, and built-in tutorial systems could make BigQuery more accessible to a broader audience.
We are committed to Caspio Bridge. We could migrate to another product, but we would not be able to do so quickly. I estimate that we would need about a year (maybe more) to convert all of our forms and processes if we were to switch to some other product
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
I've had some instances where my team and I discovered a bug in Caspio. We alerted the company, and the bug was fixed in the next regular update of the software. The few times that I've had to contact support, it was a pretty good experience. They're not terribly quick to respond and take action, but they don't ignore you, either.
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
GroupHigh is so frustrating to use. It is constantly changing the way you can search for bloggers, and we can never find exactly what we are looking for
I have used Snowflake and DataGrip for data retrieval as well as Google BigQuery and can say that all these tools compete for head to head. It is very difficult to say which is better than the other but some features provided by Google BigQuery give it an edge over the others. For example, the reliability of Google is unmatchable by others. One thing that I really like is the ability to integrate Data Studio so easily with Google BigQuery.
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
Pricing has been very reasonable for us. The first 10 GB of storage is free each month and costs start at 2 cents per GB per month after that. For example, if you store 1 terabyte (TB) for a month, then the cost would be $20. Streaming data inserts start at 1 cent per 200 megabytes (MBs). The first 1 TB of queries is free, with additional analysis at $5 per TB thereafter. Meta data operations are free.
Big Query helps reduce the bar for data analytics, ML and AI. BQ takes care of mundane tasks and streamlines for easy data processing, consumption. The most impressive thing is the ML and AI integration as SQL functions, so the need for moving data around is minimized.
The visuals of ML models is very helpful to fine tune training, model building and prediction, etc.
